Theoretical Connections Research Articles

Improving forward compatibility in class incremental learning by increasing representation rank and feature richness

Class Incremental Learning (CIL) constitutes a pivotal subfield within continual learning, aimed at enabling models to progressively learn new classification tasks while retaining knowledge obtained from prior tasks. Although previous studies have predominantly focused on backward compatible approaches to mitigate catastrophic forgetting, recent investigations have introduced forward compatible methods to enhance performance on novel tasks and complement existing backward compatible methods. In this study, we introduce effective-Rank based Feature Richness enhancement (RFR) method that is designed for improving forward compatibility. Specifically, this method increases the effective rank of representations during the base session, thereby facilitating the incorporation of more informative features pertinent to unseen novel tasks. Consequently, RFR achieves dual objectives in backward and forward compatibility: minimizing feature extractor modifications and enhancing novel task performance, respectively. To validate the efficacy of our approach, we establish a theoretical connection between effective rank and the Shannon entropy of representations. Subsequently, we conduct comprehensive experiments by integrating RFR into eleven well-known CIL methods. Our results demonstrate the effectiveness of our approach in enhancing novel-task performance while mitigating catastrophic forgetting. Furthermore, our method notably improves the average incremental accuracy across all eleven cases examined.

Online in situ detection of deposited height deviation during additive manufacturing

Deposited height deviation (DHD) of printed layers is a common surface defect that restricts vertical printing accuracy during the additive manufacturing process. The accumulation of DHD layer by layer inevitably leads to the failure of subsequent additive manufacturing tasks. Therefore, accurate online measurement of DHD is crucial. This study proposed a novel amplification computer-vision measurement (ACVM) method that effectively utilizes both melt pool images and temperature information, achieving a DHD detection sensitivity of approximately 9.96 μm. Theoretical connections between image features and DHD, as well as the theoretical associations between instantaneous temperature characteristic and DHD, have been systematically deduced. Based on these two theoretical relationships, DHD can be accurately and synchronously detected directly through the positions of image features and temperature. A single-camera dual-channel multi-signal detection (SDMD) system was developed and implemented within a laser-engineered net shaping (LENS) additive manufacturing system. Subsequently, an online measuring and verification experiment was designed to assess the height deviation of thin-walled structural parts. The experimental results demonstrated that the ACVM method provided an early response to DHD. The method exhibits significant technical application value in quality control in future.

Exploring the ‘Invisible’ in GTAs: Reflections on Intuition and Post-Graduate Mentoring

Postgraduate researchers who teach (Graduate Teaching Assistants) always navigate their academic spaces among several psychological factors in their routines from both inside and outside. They can often be observed attending to students, advising them on their problems and sometimes even relying on their seniors for various topics. In such situations, practitioner intuition remains a well-known and relied-upon source of GTA's decision-making skills but also an underexplored area of investigation, especially in mentoring and language teaching literature (Ushioda, 2023; Burns & Williams, 2023 & Kumar, 2024). Based on this premise, this reflective paper aims to simplify and understand the GTA's pedagogic intuition towards success and failures in PG thesis writing contexts from peer-mentoring perspectives. The initial sections of the paper, imagining GTA's as mentors and their learners as mentees, establish what GTA intuition can be thought of, how it is related to Vygotsky's ZPD (Zone of Proximal Development) and the potential operations based on an intuitive decision-making model. The latter part of the paper offers detailed practical insights about these theoretical connections through my own workings of intuition while scaffolding the PG mentees to plan, execute and write their theses. Detailed reflections of both the GTA/mentor and the mentees elicited through think-aloud and discursive puzzling measures are reported extensively. Lastly, the paper advocates for more work towards exploring GTA's intuition in mentoring scenarios (and otherwise), getting more awareness from their cognitions and becoming more intuitive practitioners.

Mind wandering is associated with worsening attentional vigilance.

The tendency for our minds to wander is a pervasive and disruptive influence on continued task performance. Models of sustained attention have implicated mind wandering, moments when attention has turned inwards toward task-unrelated thought, in characteristic patterns of worsening performance with greater time-on-task, known as the vigilance decrement. Despite their theoretical connection, associations between mind wandering and the vigilance decrement have not been investigated systematically. Across two studies (N = 730), we evaluated covariance between within-task change in rates of probe-caught mind wandering and patterns of worsening behavioral task performance that characterize the vigilance decrement. Bivariate growth curve models characterized patterns of intraindividual linear change in mind wandering alongside concomitant changes in task accuracy, response time (RT), and RT variability. Importantly, models assessing the covariance between intraindividual change in mind wandering and behavioral outcome measures confirmed that increases in mind wandering are associated with patterns of worsening behavioral performance with greater time-on-task. In addition, we investigated the role of several moderating factors associated with patterns of within-task change: self-reported task interest and motivation, and individuals' propensity for mind wandering, and mindfulness in their daily lives. These factors moderated either the overall level or rate of within-task change in mind wandering. Our results provide support for models of sustained attention that directly implicate mind wandering in worsening behavioral performance with greater time-on-task in continuous performance tasks requiring sustained attention. (PsycInfo Database Record (c) 2024 APA, all rights reserved).

Exploring action-oriented models via active inference for autonomous vehicles

Being able to robustly interact with and navigate a dynamic environment has been a long-standing challenge in intelligent transportation systems. Autonomous agents can use models that mimic the human brain to learn how to respond to other participants’ actions in the environment and proactively coordinate with the dynamics. Modeling brain learning procedures is challenging for multiple reasons, such as stochasticity, multimodality, and unobservant intents. Active inference may be defined as the Bayesian modeling of a brain with a biologically plausible model of the agent. Its primary idea relies on the free energy principle and the prior preference of the agent. It enables the agent to choose an action that leads to its preferred future observations. An exploring action-oriented model is introduced to address the inference complexity and solve the exploration–exploitation dilemma in unobserved environments. It is conducted by adapting active inference to an imitation learning approach and finding a theoretical connection between them. We present a multimodal self-awareness architecture for autonomous driving systems where the proposed techniques are evaluated on their ability to model proper driving behavior. Experimental results provide the basis for the intelligent driving system to make more human-like decisions and improve agent performance to avoid a collision.

Free Speech, Green Power: The Impact of Freedom of Expression on Renewable Energy

Although there has been a growing interest in identifying the key drivers of renewable energy over the last few decades, theoretical connections and empirical evidence on the impact of freedom of expression still need to be made. Within the framework of this gap in the literature, this study tries to solve the mystery by focusing on the impact of freedom of expression on renewable energy in 20 high-income countries from 1990 to 2022. The effects of economic growth, carbon dioxide emissions, trade openness, and foreign direct investment were also examined. The evidence-based on second-generation econometric estimators such as AMG and CCEMG are consistent. Findings show that freedom of expression indicates increased renewable energy consumption. In addition, while economic growth and foreign direct investments increase renewable energy, CO2 emissions reduce renewable energy. Trade has no significant impact. The positive link between freedom of expression and renewable energy is promising for the countries involved and presents a significant win–win opportunity. Therefore, countries need to establish democratic principles.

Big data analytics, GHRM practices, and green digital learning paving the way towards green innovation and sustainable firm performance

This research aims to understand the connections among Green Human Resource Management (GHRM) practices, Green Digital Learning Orientation (GDLO), Green Innovation (GI), and Sustainable Firm Performance (SFP) in small and medium-sized enterprises (SMEs) of Saudi Arabia. The data were analyzed utilizing the PLS-SEM approach, whereas data from 341 SMEs was examined. The study findings reveal significant positive relationships between GHRM and GI, GDLO and GI, GHRM practices and GDLO, and GI and SFP. The study supports the mediating role of green innovation in these relationships. Big data analytics is found to moderate the connections between GHRM-GI and GDLO-GI. This study is the first to establish the theoretical connection with the AMO model by emphasizing how GHRM and innovation enhance sustainable firm performance. Also, practical implications guide SMEs in integrating GHRM practices, raising a culture of innovation, and acknowledging the pivotal role of employees. The study recognizes limitations, urging future research to consider external factors and address gaps in the literature on GHRM practices in SME sustainable firm performance in the Gulf region.

The Relationships between Influencers and Followers Who Troll and Proactive‐Reactive Trolling

ABSTRACTLittle is known about the differences between trolling by influencers and followers, the difference between proactive and reactive trolling, and the relationship between them. Based on a content analysis of 1,386 comments on 160 posts of 19 influencers during a Sina Weibo trolling event, we found that influencers troll more frequently than their followers and they troll proactively more often than reactively, while followers troll reactively more often than proactively. Influencers generated less but more impactful content compared with their followers. In both proactive and reactive trolling, influencers derailed the discussion while followers provoked through their proactive trolling and insulted through their reactive trolling. These findings extend the research scope of trolling asymmetry and establish theoretical connections between social media roles and proactive‐reactive trolling.

My Theory, my Tool, my Tribe: Unpacking Scholars’ Perspectives on the Evolution of Transformative Learning

Tracking the evolution of transformative learning theory (TLT) has primarily been conducted through literature review while overlooking potential insights from empirical meta-studies. We examined evolving perspectives on TLT through a meta-analysis of scholars’ engagements within the field. We incorporated narrative interviews with twelve scholars, using thematic analysis to draw insights from their experiences and contributions. Employing the Community of Practice (CoP) framework, we explored the collective shaping of TLT by its academic community, exploring themes such as critical and appreciative views on Mezirow and TLT foundational concepts, the theory’s application in research and teaching, its theoretical connections, its geographical expansion, publication contributions, and community building. The findings highlighted the dynamic and socially constructed nature of transformative learning field and its adaptability to diverse contexts and contemporary challenges. The study underscored the importance of collaboration and community building among scholars, which not only sustains the theory but also propels its evolution, ensuring its continued relevance. Moving forward, we advocated for continued innovation in theory and practice within the transformative learning community.

A Systematic Literature Review of Existing Methods and Tools for the Criticality Assessment of Raw Materials: A Focus on the Relations between the Concepts of Criticality and Environmental Sustainability

Critical raw materials have significant economic and social impacts across numerous sectors. Numerous artifacts have been developed to assess their criticality. However, there is no univocity around the factors determining criticality. A systematic literature review was conducted to consider all academic works and official reports on criticality assessment. The review aimed to classify these artifacts to provide a clear picture of the heterogenous literature, with a focus on the relationship between criticality and environmental sustainability. Works proposing or updating criticality assessment artifacts were included according to the eligibility criteria. Academic sources were drawn from the Scopus Database in 2023. Official reports included those considered seminal by academic literature. The risk of bias in the selection and classification of the 162 works was low, as the review sought to be comprehensive. The included artifacts are systematically classified. A mapping of the identified criticality assessment tools and methods has been developed. The review found that while environmental impacts are considered in several works, the theoretical connection between criticality and environmental sustainability is weak. Three perspectives on this relationship are identified and discussed. The main limitation of this study is the inability to analyze undisclosed artifacts. It was conducted under the Horizon Europe Programme (Grant Number 101091490).

Cricket Australia’s Code of Conduct and the need for a ‘clear family resemblance’ in purpose, values, and principles

ABSTRACT This article examines Cricket Australia’s (CA) Code of Conduct and draws theoretical connections to Enterprise Risk Management (ERM). In so doing, the article considers the nature and scope of CA’s Code of Conduct, and challenges for the effective implementation of the code. The purpose of a Code of Conduct is to set out expectations for behaviour and disciplinary processes for failure to adhere to these standards. However, while public image and popularity remain central objectives of the Code, there is ambiguity and conflict between these objectives and the third objective: integrity, an ethical value that underpins codes of conduct. Our recommendation to remove public image and popularity from the purpose of the Code of Conduct is consistent with The Ethics Centre 2018 Report that recommended a ‘core consistency (a clear ‘family resemblance’) between How We Play, the Spirit of Cricket, and any additional Ethical Framework applying to elite players’. We suggest that ‘core consistency’ starts with a clear and consistent purpose in the Code of Conduct, one that is not clouded by public image and popularity, and one that is focused on the ethical values of integrity, transparency, and accountability.

Active Inference and Reinforcement Learning: A Unified Inference on Continuous State and Action Spaces Under Partial Observability.

Reinforcement learning (RL) has garnered significant attention for developing decision-making agents that aim to maximize rewards, specified by an external supervisor, within fully observable environments. However, many real-world problems involve partial or noisy observations, where agents cannot access complete and accurate information about the environment. These problems are commonly formulated as partially observable Markov decision processes (POMDPs). Previous studies have tackled RL in POMDPs by either incorporating the memory of past actions and observations or by inferring the true state of the environment from observed data. Nevertheless, aggregating observations and actions over time becomes impractical in problems with large decision-making time horizons and high-dimensional spaces. Furthermore, inference-based RL approaches often require many environmental samples to perform well, as they focus solely on reward maximization and neglect uncertainty in the inferred state. Active inference (AIF) is a framework naturally formulated in POMDPs and directs agents to select actions by minimizing a function called expected free energy (EFE). This supplies reward-maximizing (or exploitative) behavior, as in RL, with information-seeking (or exploratory) behavior. Despite this exploratory behavior of AIF, its use is limited to problems with small time horizons and discrete spaces due to the computational challenges associated with EFE. In this article, we propose a unified principle that establishes a theoretical connection between AIF and RL, enabling seamless integration of these two approaches and overcoming their limitations in continuous space POMDP settings. We substantiate our findings with rigorous theoretical analysis, providing novel perspectives for using AIF in designing and implementing artificial agents. Experimental results demonstrate the superior learning capabilities of our method compared to other alternative RL approaches in solving partially observable tasks with continuous spaces. Notably, our approach harnesses information-seeking exploration, enabling it to effectively solve reward-free problems and rendering explicit task reward design by an external supervisor optional.

Crimes Omissions: A Psycho-Sociological Perspective

This research was based on understanding and managing crimes of omission is a key strategy for reducing their harmful effects. The research aim was to analyze the personal and social characteristics of individuals responsible for crimes committed by inaction in Georgia. The study employed a mixed-methods approach to explore the psycho-sociological foundations of inaction and was conducted in two stages. The first stage discussed the theoretical framework surrounding inaction, while the second stage analyzed cases of inaction in Georgia. During the research process, significant gaps in public data were identified, highlighting the challenges of recording and accessing information about these crimes. Despite these challenges, a strong theoretical and empirical connection was identified between crimes of omission and the broader context of cultural and social passivity in developing post-Soviet Georgian society. This connection underscores the significant impact of the post-Soviet legacy in understanding the legal and psychosocial context of crimes of omission. As a result, to reduce crimes of omission and increase public involvement, the study suggests improving the judicial system, promoting legal knowledge, and encouraging civic activism and initiative within society.

Effect of government environmental attention on green transformation: Empirical analysis from a spatiotemporal perspective in China

As the primary policymaker and implementer, the government plays an essential role in driving regional green transformation development (GTD). The study of the impact mechanisms of government environmental attention (GEA) on GTD can offer a scientific basis and reference for policy-making and regional governance. However, the varying focus of local governments on environmental issues and the externalities of environmental governance underscore the complexities in the influence of GEA on GTD. This paper proposes a method that integrates multi-source data to explore the impact of GEA on GTD from a spatiotemporal perspective. A text mining framework is first proposed to provide a more accurate measurement of the GEA, and the geographically and temporally weighted regression model is used to analyze the spatiotemporal characteristic and mechanism of GEA's impact. Additionally, the spatial correlation effect is explored based on the gravity model. The results indicate that the level of GTD in China demonstrates an increasing trend with an average annual growth rate (AAGR) of 3.22%, while the variance between provinces is also increasing. GEA has a significant positive effect on GTD (R2 = 0.866), with an average growth rate of 18.1% following the implementation of major environmental policies. The spatial distribution pattern of GEA's impact shows the characteristics of “central > eastern > western > northeastern”. GEA promotes GTD by increasing environmental governance expenditure and enhancing public environmental services, while the transmission pathway of promoting green innovation has not yet worked. The spatial correlation and spillover effects of GEA have shown an overall increasing trend, with the AAGR of 8.92% in the gravity value. Inter-provincial cooperation can promote GTD, and certain collaborative clusters among provinces have been formed. This paper provides novel insights into the theoretical connection between GEA and GTD. The research findings can serve as a reference for the government to propose targeted policies for promoting regional green transformation.

The Five-Year Plan and target allocation cycle of environmental pollution in China

SummaryThis paper establishes a theoretical connection between China’s Five-Year Plan (FYP) and environmental pollution. We propose a target allocation cycle theory to explain the periodic feature of environmental pollution, which advances political business theory in different institutional contexts. By analysing industrial SO2 and PM2.5 data as well as the political career data of officials in 277 Chinese cities from 2003 to 2019, we reveal a significant influence of China’s political business cycles, as dictated by the FYP, on the periodicity of environmental pollution. Specifically, the emissions of industrial SO2 and PM2.5 exhibit a U-shaped periodic trend, peaking during the initial 2 years of each FYP, followed by a gradual decline in subsequent years, only to peak again in the first year of the succeeding FYP. These findings suggest that local political leaders strategically allocate their efforts in managing environmental pollution. Initially, there is a relaxation of environmental regulation during the early stages of a FYP, which is then followed by a shift towards more stringent environmental governance after the midpoint of the FYP.

Platforming the Joe Rogan Experience: Cancel Culture, Comedy, and Infrastructure

This paper outlines a cultural critique of the Joe Rogan Experience. Framing the podcast as an adaptive cultural platform, I emphasize how it is ideologically informed by both the established infrastructure and dynamics of communicative capitalism and Joe Rogan’s ethos as a comedian. The paper discusses three ways Joe Rogan and his format negotiate their relationship with platform infrastructures. The first is Rogan’s relationship with Spotify and his interest in shaping “cancel discourses” and, subsequently, his own role as an embedded, “uncancellable” skeptic. The second is the combination of Rogan’s roast universalism and pioneering speech-a-ton format, designed to establish an infrastructure for platforming his cohort of podcasting comedians on YouTube. The third is Rogan’s relationship with platform-owner Elon Musk, whose communicative capitalist agenda has political implications. The paper establishes a theoretical connection between studies of platformisation and the under-studied cultural influence of podcasting comedians.

Comparison Between Balance Ability and Muscle Endurance Among Patient with Shoulder Impingement

Abstract Aim; Chronic pain has been theorized to hinder balance control by compromising muscle endurance. Despite this theoretical connection, there is limited empirical evidence on this phenomenon, especially in patients diagnosed with shoulder impingement. This study aims to investigate muscle endurance, balance measures, and indicators of shoulder dysfunction in patients with impingement, comparing them with age- and sex-matched healthy controls. Method; In this cross-sectional study, patients (n=31) with shoulder impingement and healthy controls (n=23) matched for age and gender were compared with regard to their balance ability and physical performance. Functional questionnaires (Disabilities of the Arm, Shoulder, and Hand (DASH) as well as Single-Leg Stance Balance Test (SLBT), Y Balance test, Scapular Endurance Test, Trunk muscle flexor and extensor test, grip strength and Nine-Hole Peg Test (NHPT) were completed in a randomized order with consistent raters. Results; Patients with shoulder pain showed significantly worse results in measurements of shoulder function (p

An Overview of Theoretical Connections between the Rhetoric of Modernity and Postmodernity

This paper explores the thematic convergences and departures within the rhetoric of modernity and postmodernity. In doing so, it explores some of their key themes such as language and meaning, reality and truth, autonomy and human progress, and reason concerning the works of Jurgen Habermas, John Locke, Jacques Derrida, Ferdinand de Saussure, Immanuel Kant and Jean Francois Lyotard. This paper employs a methodology of comparative textual analysis of the aforementioned authors’ selected texts and their themes in their historical/temporal positions within the discourse of the rhetoric of modernity and postmodernity. It fulfills two objectives: to explore what recurrent themes of modernity and postmodernity appear in the canonical theorists’ works, and to assess how they simultaneously overlap and differ from each other. Stepping on this comparative analysis, this paper brings together the thematic and theoretical connections between the rhetoric of modernity and postmodernity to conclude that the similarities and differences in the rhetoric of modernity and postmodernity among the selected theorists can be revisited through a thematic lens rather than the historical-temporal paradigms.

Assessing the strategic role of urban green spaces for habitat connectivity in multi-family residential plots

Urban green spaces are key for maintaining and restoring habitat connectivity within cities. Despite substantial investigations on the contribution to connectivity of different types of urban green spaces, the specific contribution of green spaces located in multifamily residential (MFR) plots has yet to be assessed. Estimating this contribution is crucial given the multiple roles fulfilled by these green spaces in urban planning. To achieve this goal, we focused on four taxa: the European hedgehog (Erinaceus europaeus), the Red squirrel (Sciurus vulgaris), forest passerine birds and moths. We assessed the potential habitat connectivity for each taxon across the metropolitan urban area of Lyon (France), with landscape graphs built using 1-metre resolution land cover maps. Considering the current state as a reference, we then designed five land cover change scenarios affecting habitat distribution in the MFR plots: (i) maximum and (ii) minimum theoretical connectivity (references), (iii) improve quality of existing green spaces, (iv) improve quantity of green spaces with sub-optimal quality and, (v) maximum restoration (management scenarios). The taxon- and scenario-specific impacts highlight the crucial contribution of private spaces to habitat connectivity. For all taxa, while the MFR only cover 8 % of the study area, connectivity would increase by up to 60 % if these plots were greened. In contrast, sealing these plots could reduce overall connectivity by up to 40 %. The interpolation of local connectivity metrics for each habitat patch and each MFR plot allowed us to identify the most relevant plots for urban greening. Because our approach can improve habitat connectivity at different scales, from neighbourhoods to entire urban areas, it could prove useful for landscape planning in most urban settings.

Genieys, William & Darviche, Mohammad-Saïd (2023). Elites, Policies and State Reconfiguration. Transforming the French Welfare Regime. Cham: Switzerland. 198 Seiten. ISBN: 978-3-031-41582-1.

This book takes the hierarchical political system in France as a starting point to analyze the influence of elites on the reconfiguration of state and policy processes. Major reform developments in social policy are attributed to actors’ biographies and changing constellations. While the book thereby offers a detailed account of social policy reforms and individual backgrounds, it lacks a theoretical connection to the broader public policy research literature beyond elite sociology and path dependency. Thereby, a systematic and theoretically guided identification of mechanisms that link actor dynamics and policy outcomes is missing. Nevertheless, the impressively comprehensive interview data from several decades provides invaluable insights into influential actors within the state, serving as a resource for researchers, lecturers, and practitioners.